Download evaluation of cirrhosis liver disease via protein-protein

EVALUATION OF CIRRHOSIS LIVER DISEASE VIA PROTEIN-PROTEIN INTERACTION
NETWORK
Akram Safaei1, Mostafa rezaei tavirani1,*,Afsane Arefi Oskouei1, Mona Zamanian Azodi1 , Seyed Reza Mohebi2 and Abdol Rahim
Nikzamir3
1., Proteomics Research Center, Faculty of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
2. Gastroenterology and liver diseases research center, Shahid Beheshti University of Medical Sciences, Tehran, Iran
3.Faculty of medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
Email: [email protected]
ABSTRACT
In clinical usage, liver biopsy remains the gold standard for diagnosis of hepatic fibrosis.
Evaluation and confirmation of hepatic fibrosis stages and progression in chronic diseases still face
by lack of decisive and stout noninvasive biomarkers. So, the early diagnosis of cirrhosis is a
problem for the clinician, and it have been afforded to present sensitive, specific and predictive
novel biomarkers that can identify and detect early stage of the disease. In this article, to gain a
better perception, biological characteristic of 13 identified proteins that were extracted from
proteomic data of human cirrhotic liver which likely to be involved in disease was evaluated.
Required analysis such as gene ontology (GO) enrichment and protein-protein interactions (PPI)
analysis undergo EXPASy , STRING Database and DAVID Bioinformatics Resources query.
Based on GO analysis, the most of the proteins are located in endoplasmic reticulum lumen,
intracellular organelle lumen, membrane-enclosed lumen and extracellular region. Actin binding,
metal ion binding, cation binding and ion binding and biological processes including cell adhesion,
biological adhesion, cellular amino acid derivative metabolic process, chemical homeostasis and
homeostatic process are related function and processes. Protein-protein interaction network analysis
introduced five proteins (fibroblast growth factor receptor 4, tropomyosin 4, tropomyosin 2 (beta),
lectin, galactoside-binding, soluble, 3 binding protein and apolipoprotein A-I) as hub and bottleneck
proteins. It seems more investigation about these marked proteins will provide better understanding
about cirrhosis disease.
Keywords: cirrhosis, gene ontology, Protein-protein interaction network, DAVID Bioinformatics
Resources 6.7, STRING
 Corresponding author
INTRODUCTION
Cirrhosis is the development stage of liver fibrosis. In fibrosis damage tissues replace by collagen
layer that cause deficiency of the liver cells function. Decompensated cirrhosis may cause to
hepatocellular carcinoma (HCC) (1). HCC is the most common intra-abdominal malignancy in the
world (2). Another way, mortality range of liver cancer based on cirrhosis are developed(3). Liver
Parenchymal cells are damaged by inflammatory reaction that cause to induce synthesize collagen,
chemokines and a broad range of inflammatory and anti-inflammatory cytokines (4). In Cirrhosis
disrupt normal liver architecture by both fibrotic bands and disorganized nodules. Unfortunately,
There is presently no medical treatment to rebound the changes of cirrhosis (5). It usually occurs as
a complication of a previous liver disease, such as chronic hepatitis B or C viruses (6). Presently
the diagnostic information for cirrhosis is based on the combined results of clinical test and
imaging (1, 7). However, because of some limitations, these methods cannot be satisfactorily
applied to a sensitive clinical diagnosis (8, 9). The liver biopsy is a standard, but an invasive
approach to diagnose liver diseases. Efforts have been focused on finding sensitive and specific
predictive markers to early and non-invasive diagnosis of hepatic diseases (10). For this,
recognition of cirrhotic molecular pathways and their relations can help more understanding of
pathophysiological liver disease, early stage diagnosis and treatment in time. In recent years ,
related genes with cirrhosis have been introduced such as acetyltransferase 2, apolipoprotein C-III,
calponin 1, microfibrillar-associated protein 4, complement complement 7, lectin, galactosidebinding, soluble, 3 binding protein , lectin, galactoside-binding, soluble, 4 (Galectin-4), prolyl 4hydroxylase, alpha polypeptide I, apolipoprotein A-I, apolipoprotein A-IV, transgelin, tropomyosin
2 and tropomyosin 4(5, 11-15). Introducing biomarker panel for some diseases is a significant
activity in the field of diagnosis and therapeutic aspects of medicine(16). Bioinformatics is one of
the new techniques in research of modern world that analysis high throughput data in few time(17).
Enrichment analysis of the interest proteins can be helpful in understanding the significant intricate parts
of the cells and the underling mechanism of the disease pathology (18, 19). In this study, the
enrichment analysis of identified proteins based on GO and PPI are investigated for cirrhosis.
Therefore, it is proposed to introduce some molecular biomarkers (as a panel) related to cirrhosis.
MATERIAL AND METHOD
The related and reported proteins in Google Scholar and PubMed collected. The referenced proteins
selected from compression of protein expression between cirrhosis patients with parallel controls.
The tools analysis are STRING 9.1 (http://string-db.org/), Uniprot protein database
(www.uniprot.org),
EXPASY and DAVID Bioinformatics Resources (v 6.7) (http://david.abcc.ncifcrf.gov.).
The name of related proteins searched in uniprot and then the codes were extracted. The codes used
in DAVID Bioinformatics Resources for GO analysis. A pack of gene annotations (e.g. functions,
processes) can help identify interesting features, but this is impossible because of large sets that it
causes difficulty in selecting statistically significant trends from large datasets. Thus, a method is
required for the routine analysis of such datasets. Gene Ontology (GO) as a common vocabulary for
annotation allows identification of semantically related genes and gene products (20).There are
separated hierarchies for Molecular Functions (MF) , Cellular Components (CC) and Biological
Processes(BP) (21). In fact, DAVID Gene Functional Classification Tool (
http://david.abcc.ncifcrf.gov ) provides a list of associated biological terms into organized classes of
related genes by using a novel algorithm (22). Functional annotation software DAVID online
program can provide functional information as clusters of sets of biological terms with similar
meaning (23-25). Protein–protein associations can provide a clear point by grouping and organizing
all protein-coding genes in a genome that can be assembled into a large network(26). The STRING
database is designed in order to assemble and evaluate protein–protein association information(27).
STRING 9.1 was used for illustration of predicted interactions of the identified proteins and
neighbor genes(28, 29). The PPI network was visualized using the Cytoscape 3.2.1 software.
MINT, Reactome-Fls, databases were used for this topology visualization.
RESULT
The selected reported cirrhosis proteins and their Uniprot IDs are tabulated in table 1.
The provided Gene ontology (GO) information including biological processes (BP), cellular
components (CC), and molecular function (MF) of the proteins are identified and illustrated in table
2 The studied proteins based on GO annotation clustered in five groups by using of DAVID
program (see table 3).
Table 1: The selected cirrhosis proteins and their Uniprot IDs
Gene type
apolipoprotein A-I
apolipoprotein A-IV
apolipoprotein C-II
calponin 1
complement 7
fibroblast growth factor receptor 4
lectin, galactoside-binding, soluble, 3 binding protein
lectin, galactoside-binding, soluble, 4 (Galectin-4)
Uniprot ID
P02647
P06727
P33622
P51911
P10643
P22455
Q08380
P56470
microfibrillar-associated protein 4
prolyl 4-hydroxylase, alpha polypeptide I
Transgelin
tropomyosin 2 (beta)
tropomyosin 4
P55083
P13674
Q01995
P07951
P67936
Table2: The selected cirrhosis proteins and their correspond gene ontology information
Molecular Function
Cellular Component
Biological Process
Molecular Function
Cellular Component
Biological Process
Molecular Function
Cellular Component
Biological Process
Molecular Function
Cellular Component
Biological Process
Molecular Function
Cellular Component
Biological Process
Molecular Function
Cellular Component
Biological Process
Molecular Function
Cellular Component
Biological Process
Molecular Function
Cellular Component
Biological Process
Molecular Function
Cellular Component
Biological Process
Molecular Function
Cellular Component
Biological Process
Molecular Function
Biological Process
Molecular Function
Cellular Component
Biological Process
Molecular Function
Cellular Component
Biological Process
Uniprot ID: P02647
Steroid binding, sterol binding, lipoprotein(receptor) binding, lipid binding, cholesterol binging,(lipid, sterol, cholesterol ) transporter activity
Extracellular region, endoplasmic reticulum(lumen),plasma membrane, organelle lumen, extracellular region part, intera cellular organelle lumen
Regulation of protein amino acid phosphorylation, immune response , cholesterol , steroid and lipid, metabolic process , cell motion, G-protein coupled receptor protein
signaling pathway, regulation of hormone levels, very-low-density lipoprotein remodeling,, cellular amino derivative metabolic process, cholesterol homeostasis, positive
regulation of catalytic activity, regulation of system process, cell motility, chemical homeostasis, regulation of cytokine secretion , protein stabilization, negative regulation of
cellular component organization, trans membrane transport, lipid homeostasis, sterol homeostasis, regulation of cellular localization, macromolecular complex assembly
Uniprot ID: 06727
Transporter activity for lipid, sterol and cholesterol, lipid binding, ion binding, cation binding, amine binding, alcohol binding, metal ion binding
extracellular region, extracellular space, endoplasmic reticulum lumen, membrane-enclosed lumen, protein-lipid complex, plasma lipoprotein particle, very-low-density
lipoprotein particle, high-density lipoprotein particle, chylomicron, , extracellular region part, intracellular organelle lumen
Cellular response to oxidative stress, cellular amino derivative metabolic process, regulation of system process, metabolic process, immune response, cell adhesion, leukocyte
adhesion, cell – cell adhesion, regulation of cholesterol absorption, regulation of lipid catabolic process, regulation of molecular function and assembly subunits, regulation off
fatty acid biosynthetic process, chemical hemostasis, catabolic process, lipid hemostasis, sterol hemostasis
Uniprot ID: P33622
Llipid binding
extracellular region, extracellular space, protein-lipid complex, plasma lipoprotein particle, very-low-density lipoprotein particle,
particle, chylomicron
lipoprotein trygriceride mobilization, lipid transport, lipid localization, catabolic process of lipid , glycerol , acyl glycerol and triglyceride
Uniprot ID: P51911
Actin binding, calmodulin binding, cytoskeleton protein binding
triglyceride-rich
lipoprotein
Cytoskeleton
cytoskeleton organization, actin filament-based process, actin cytoskeleton organization, actomyosin structure organization, regulation of system process
Uniprot ID: P10643
Actin binding, calmodulin binding, cytoskeleton protein binding
Extra cellular region, membrane attack complex, plasma membrane
lymphocyte mediated immunity, acute inflammatory response , proteolysis, cellular ion homeostasis complement activation, ,cell death, B cell mediated immunity, cellular
homeostasis, cytolysis, cellular , homeostatic process1, chemical homeostasis, ion homeostasis, protein maturation, metal ion homeostasis, sodium ion homeostasis, cellular
chemical homeostasis
Uniprot ID: P22455
Nucleotide binding, ATP binding, fibroblast growth factor binding, growth factor binding, protein kinase activity
plasma membrane, integral to plasma membrane, integral to membrane, intrinsic to membrane, intrinsic to plasma membrane, plasma membrane part
Cell fate specification, cell surface receptor linked signal transduction, cell- cell signaling, phosphorylation, developmental induction, cell proliferation, respiratory system
development
Uniprot ID: Q08380
scavenger receptor activity
extracellular region, proteinaceous extracellular matrix, extracellular space, extracellular matrix, extracellular region part
defense response, cell adhesion, biological adhesion
Uniprot ID: P56470
sugar binding
cytosol, plasma membrane
cell adhesion, biological adhesion
Uniprot ID: P55083
Fibrinogen, alpha/beta/gamma chain, C-terminal globular, Fibrinogen, alpha/beta/gamma chain, C-terminal globular, subdomain 1
micro fibril, extracellular region, extracellular matrix, fibril, extracellular matrix part
cell adhesion, biological adhesion
Uniprot ID: P13674
cellular amino derivative metabolic process, iron ion binding, oxidoreductase activity, vitamin binding, peptidyl-prolin 4 dioxygenase activity, ion binding, cation binding, metal
ion binding, transition metal ion binding
mitochondrion, endoplasmic reticulum, endoplasmic reticulum lumen, membrane-enclosed lumen, organelle lumen, endoplasmic reticulum part, intracellular organelle lumen,
cellular amino derivative metabolic process , peptidyl-proline modification , collagen organization,oxidation reduction, extracellular structure and matrix organization
Uniprot ID: Q01995
actin binding, cytoskeletal protein binding
muscle organ development
Uniprot ID: P07951
structural molecular activity, actin binding, cytoskeletal protein binding, structural constituent of muscle
cytoskeleton, muscle thin filament tropomyosin, striated muscle thin filament, actin cytoskeleton, myofibril, sarcomere, (intracellular)non-membrane-bounded organelle
regulation of hydrolase activity, regulation of ATP activity
Uniprot ID: P67936
actin binding, cytoskeletal protein binding, structural molecular activity calcium ion binding, structural constituent of muscle , ion binding, cation binding, metal ion binding
cytoskeleton, muscle thin filament tropomyosin, striated muscle thin filament, actin cytoskeleton, myofibril, sarcomere, cytoskeletal part, contractile fiber part
cell motion
Table 3: Highly integrated enrichment clustering based on GO annotation for the selected proteins by the use of
DAVID program
The integrated protein-protein interaction network was obtained from MINT, Reactome-Fls, and
STRING databases by the application of Proteomics Standard Initiative Common QUery InterfaCe
(PSICQUIC) source (figures 1,2 and 3). As it is shown in table 4, based on centrality parameters of
network (Degree and Betweeness), fibroblast growth factor receptor 4 (FGFR4), tropomyosin 4
(TPM4), tropomyosin 2 (beta) (TPM2), lectin, galactoside-binding, soluble, 3 binding protein
(LGALS3BP) and apolipoprotein A-I (APOA1) are identified as hubs and bottlenecks (and also as
hub-bottleneck elements) of network (table 4).
Figure1. PPI network for cirrhosis obtained from MINT, Reactome-Fls and STRING databases by the
application of Proteomics Standard Initiative Common QUery InterfaCe (PSICQUIC) source for the selected
proteins. Network consists of 642 nodes and 926 edges. Cytoscape 3.2.1 software was used. The red colors
points are hub-bottleneck proteins (they are listed in table 4).
(b)
(a)
Figure2. The distribution implies on the presents of proteins with high centrality values computed by
Network Analyzer. The red line indicates the power law. In figure (a) the degree distribution in the scalefree network is significantly inhomogeneous. The R-squared value is computed on logarithmized values
which is equal to 0.684 and the correlation= 0.925. Proteins with high degree are in the right down region of
the plot. In figure (b) the betweenness show the distribution is more between 0.0 tile 0.9 . The R-squared
value is computed on logarithmized values which is equal to 0.338 and the correlation= 0.928. Proteins with
high betweenness are in the left down region of the plot.
Table 4. Hub-bottleneck proteins with significant centrality values, based on two fundamental centrality
properties Degree and Betweenness.
Protein name
Degree
Betweenness
FGFR4
104
0.267
TPM4
113
0.303
TPM2
125
0.209
LGALS3BP
193
0.431
APOA1
239
0.365
Evaluation of protein interactions with proteins provides excellent information about its role in the
systematic function of proteins network. STRING resource is a suitable toll for showing these
interactions (10). Here the possible interactions for the hub-bottleneck proteins by using STRING
are presented in figure 3.
Figure3. Predicted interactions for hub-bottleneck proteins (the red colored ones) with their neighboring
ones were obtained from STRING online database (http://string-db.org).
Discussion
Hepatic cirrhosis is a life-threatening disease arising from different chronic liver disorders. Liver
cancer might occur as an end stage of steatosis, inflammation, fibrosis, and cirrhosis disease (30).
Only liver biopsy provides a reliable evaluation in grading inflammation and staging fibrosis. So,
non-invasive serum biomarkers for hepatic fibrosis with high sensitivity and specificity are
needed(12). Different aspects of biological features of the interest sets of proteins can be studied by
the use of annotation methods. The analysis can be helpful to gain a better view of biological
foundation of the gene contribution in a specific phenotype. (31). Various factors such as oxidative
stress, altered nuclear receptors , cytokines signaling , mitochondrial/peroxisomal abnormality,
hepatocyte apoptosis, and leptin resistance are responsible for progression towards inflammation
and fibrosis/cirrhosis, (32-36). Peroxisome proliferator-activated receptors (PPARs) regulate a
whole spectrum of physiological functions including lipid and glucose metabolism, cholesterol and
bile acid homeostasis, regenerative mechanisms, cell differentiation and inflammatory responses
specifically in the liver. (37, 38). Dysregulations of the expression, or activity, of specific PPAR
isoforms are also accepted to represent critical mechanisms contributing to the development of a
wide range of liver diseases(39).As it is listed in table 1, there are 13 proteins related to cirrhosis
disease. However additional investigation will elevate this number in future. According to DAVID
information (see table 2) , apolipoprotein A-I and apolipoprotein C-III appropriate in PPAR
signaling pathway therefore their related proteins may play a critical role in lever diseases. Previous
studies showed that elevation of apolipoprotein AI concentration is related to the degree of liver
injury (25) . It is suggested that genetic polymorphism in FGFR4( rs351855) may be associated
with the risk of HCC coupled with liver cirrhosis(40). FGFR4 is a ubiquitous protein playing a
potential role in extracellular matrix (ECM) turnover during fibrogenesis (41) and also
contributes in MAPK signaling pathway(25). Annotation enrichment is one of the useful
methods for clarifications of datasets(42). Further understanding of these very important and
complicated pathways, including surrounding modulators, is essential for application in clinical
settings. Recent studies have indicated that MAPK signaling pathways play key roles and have
potential as therapeutic targets in liver injury(43) As findings indicates, these studied proteins are
belong PPAR signaling, MAPK signaling pathway, Endocytosis, Regulation of actin cytoskeleton,
Arginine and proline metabolism, Drug metabolism, Cardiac muscle contraction and Hypertrophic
cardiomyopathy (HCM)pathway. According to DAVID, Based on GO analysis, the most of the
proteins are located in endoplasmic reticulum lumen, intracellular organelle lumen, membraneenclosed lumen and extracellular region. Molecular function cluster in actin binding, metal ion
binding, cation binding, ion binding . Biological process involved in cell adhesion, biological
adhesion, cellular amino acid derivative metabolic process, chemical homeostasis and homeostatic
process. Adhesion molecules are cell surface glycoproteins that are critical for the localization of
leukocytes at sites of inflammation (44). In polycystic liver disease It was reported the
overexpression of growth factor receptors and loss of adhesion (45). Alterations in inflammationrelated components and soluble adhesion molecules are prognostic significance in cirrhosis disease.
Systemic inflammation
is one of the significant elements that is involved in cirrhosis
physiopathology. It is has been suggested that it plays a considerable role in the cirrhosisassociated immune dysfunction syndrome (46). Some of the studied proteins are involved in
inflammatory response. Additionally, some of the proteins are involved in lipid transporter activity
that it has been shown change in the lipid composition of cellular membranes. This process
changes plasma lipid and lipoproteins level (47). As it is depicted in tables 2 and 3 cirrhosis
disease is characterized by the vast alterations in molecular functions, cellular components and
biological processes. PPI network for cirrhosis disease (see figure 1) introduced 642 nodes and 926
edges. Topological analysis leads to determination of five hub-bottleneck proteins. These key
proteins are tabulated in table 4. A hub protein is a node with a number of links that greatly exceeds
the average (48). APOA1 as a hub protein possess highest degree value (degree is one of the
centrality parameters). ApoA1 is the main protein component of high density lipoprotein in plasma
(33) which is involvement in formation of most plasma cholesterol esters (34). A bottleneck protein
plays a critical role in integrity of network. Lectin, galactoside-binding, soluble, 3 binding protein
(LGALS3BP) is characreized with highest betweenness value (betweenness is the other parameter
of centrality properties of network). LGALS3BP is involved in defense response, cell adhesion and
biological adhesion processes. Possible interactions with neighboring proteins for hub-bottleneck
proteins (see figure 3) provided valuable information for evaluation of biological importance of
these proteins. It seems that control of expression of these five proteins has considerable effects on
pathology of cirrhosis disease. This achievement requires more investigation especially following
patients in the process of development of disease.
CONCLUSION
The finding indicated that the studied proteins are belong to PPAR signaling, MAPK signaling
pathway, Endocytosis, Regulation of actin cytoskeleton, Arginine and proline metabolism, Drug
metabolism, Cardiac muscle contraction and Hypertrophic cardiomyopathy (HCM) pathway. So
regulation of lipid metabolism and cell survival are important biological processes involved in
cirrhosis disease. Five proteins were introduced as hub-bottleneck protein. It can be concluded that
regulation of genes expression including FGFR4, TPM4 (beta), TPM2, LGALS3BP and
APOA1proteins can play a key role in pathology of cirrhosis disease.
ACKNOWLEDGMENT
This research has been derived from the Ph.D. thesis of Mrs.Akram Safaei.
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